alirezadir / Production-Level-Deep-LearningLinks
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
☆4,509Updated 2 months ago
Alternatives and similar repositories for Production-Level-Deep-Learning
Users that are interested in Production-Level-Deep-Learning are comparing it to the libraries listed below
Sorting:
- A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dm…☆9,538Updated 2 years ago
- In this repository, I will share some useful notes and references about deploying deep learning-based models in production.☆4,371Updated 9 months ago
- https://huyenchip.com/ml-interviews-book/☆3,858Updated 5 months ago
- Lab materials for the Full Stack Deep Learning Course☆1,214Updated 3 years ago
- Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.☆11,347Updated last year
- This repo is meant to serve as a guide for Machine Learning/AI technical interviews.☆6,744Updated 2 months ago
- Learn how to design, develop, deploy and iterate on production-grade ML applications.☆3,190Updated last year
- A repo for data science related questions and answers☆2,426Updated 2 years ago
- This repository is to prepare for Machine Learning interviews.☆1,580Updated 6 years ago
- Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.☆3,622Updated 5 years ago
- Full Stack Deep Learning Online Course☆901Updated 3 years ago
- Machine Learning and Computer Vision Engineer - Technical Interview Questions☆3,958Updated 3 months ago
- PyTorch tutorials and best practices.☆1,695Updated 5 months ago
- Source code accompanying O'Reilly book: Machine Learning Design Patterns☆2,024Updated 4 years ago
- VIP cheatsheets for Stanford's CS 230 Deep Learning☆6,636Updated 5 years ago
- A curated list of references for MLOps☆13,292Updated 9 months ago
- VIP cheatsheets for Stanford's CS 221 Artificial Intelligence☆2,779Updated 5 years ago
- A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)☆7,387Updated 10 months ago
- System design patterns for machine learning☆2,717Updated 3 years ago
- 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.☆2,865Updated 2 years ago
- Answers to 120 commonly asked data science interview questions.☆3,817Updated last year
- Natural Language Processing Best Practices & Examples☆6,428Updated 2 years ago
- This repo contains annotated research papers that I found really good and useful☆2,743Updated last month
- Data science interview questions with answers. Not ideally (yet)☆1,634Updated 3 years ago
- Debugging, monitoring and visualization for Python Machine Learning and Data Science☆3,451Updated last year
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning☆19,039Updated this week
- Data science interview questions and answers☆9,444Updated 4 months ago
- The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.☆12,054Updated last month
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…☆1,362Updated 7 months ago
- Preparing for machine learning interviews☆905Updated 2 years ago